Laurel Riek, associate professor of Computer Science and Engineering at the University of California San Diego, will lead a three-year National Science Foundation (NSF) project on new methods for coordinating teams of robots and people in complex, uncertain environments.

The $750,000 award is shared by UC San Diego and Northeastern University, where Riek’s collaborator, Christopher Amato, is a professor in the College of Computer and Information Science. The grant is part of the National Robotics Initiative under NSF’s Information and Intelligent Systems Division.

“We plan to develop new algorithms to support multi-human, multi-robot teaming in unknown or uncertain environments,” said Riek, who is also a member of UC San Diego’s Contextual Robotics Institute. “The project also has an important application area: helping to reduce clinical workloads in perpetually busy hospital emergency rooms.”

The decreasing cost and increasing sophistication of robot hardware is creating new opportunities for teams of robots to be deployed in combination with skilled humans to support and augment labor-intensive or dangerous manual work, according to Riek. The vision is for robots to free up time of skilled workers so they can focus on tasks at which they are most adept and most enjoy (e.g., problem solving, using human dexterity to manipulate objects, or talking to customers). Meanwhile, robots can help with the distracting or frustrating parts of work, such as delivering materials or fetching supplies.

Riek argues, however, that progress in this area is being stymied by three problems. “First, current methods are not generalizable, and require people to continually reinvent the wheel," she said. "Second, approaches are too rigid, and rely on unrealistic models of human-robot teaming, making them ineffective. Finally, few methods can cope with uncertain environments, where little can be known or planned for in advance.” This project proposes to overcome such problems by creating new methods by which a team’s robots can coordinate with their human counterparts to complete complex challenges that require both sets of capabilities.

The research will build off of previous methods that have been successful in single-robot challenges under uncertainty or partial observability, and in particular, partially observable Markov decision processes (POMDPs). With POMDPs, researchers model robots and the environment, but not humans. For the NSF-funded project, however, Riek will explicitly include people in the models. “For robots to work safely and effectively in human environments," she said, "it is critical that people are included in our models.”

The researchers plan to complete three primary contributions during the three-year project to:

Transform the concept of how multi-human, multi-robot teamwork can occur to reflect the strengths and limitations of the team in a “temporally dynamic, stochastic environment”;

Develop realistic and general models of human-robot teamwork that consider uncertainty and partial observability; and

Contribute innovative and scalable techniques for planning and learning in these models.

Critical environments are complex, non-deterministic spaces where people have high workloads, are under time constraints, and must make decisions under uncertainty. This project will focus on Emergency Departments, where staff are frequently so overburdened they can cannot complete straightforward tasks, such as fetching supplies and equipment. Example images from this domain (l-r): preparing to take a patient’s vital signs; the cluttered room which must be cleaned after a patient is transferred; a volunteer delivering a cart down a very cluttered hallway; and a supply cabinet which does not get restocked with necessities during high-volume times.

In addition to the project’s fundamental scientific contributions, Riek intends to focus on a key, real-world application space: emergency departments (ED), where time is critical and conditions change from moment to moment. “EDs involve a great deal of uncertainty, as well as many delivery and supply tasks during high-volume periods,” said Riek. “A team of robots can fluently assist with these tasks, which will free up clinicians’ time to focus on treating patients. This, in turn, will help to improve patient outcomes and safety.”

Simulation of realistic ED conditions will be carried out in the Simulation and Training Center of the UC San Diego School of Medicine. It comprises an entire bottom floor of a building, which allows trainees and providers to practice procedures, teamwork, and crisis response via high-fidelity physical clinical simulation. It contains multiple patient bays and rooms, and is populated with high-fidelity patient simulators (lifelike humanoid robots with complex physiologies, which can breathe, bleed and respond to medication). It also has a full array of resources commonly used in hospitals, such as supplies, monitoring machines, etc.